A simple and rapid nucleic acid preparation method for reverse transcription polymerase chain reaction (RTPCR) in dormant potato tubers

In order to shorten and facilitate the preparation of nucleic acid (without using tuber slicer, santurugation, vacuum devices and nanocalorimeter (NCM)) for reverse transcription polymerase chain reaction (RT-PCR), pieces of tuber were placed directly into eppendorf tubes containing 30 ìl ofdetergent (0.5% Triton XL-80 N) buffers, vortexed for 3 min and then 2.5 ìl of this aliquots was used in RT-PCR. Alternatively, evaluation of the efficiency of different buffers (sodium sulphite buffer, 0.1 M HCl, 0.1 M NaOH, 0.1 M Tris, 0.1 M EDTA, 0.1 M phosphate buffer, 0.1 M LiCl, 0.1 M KCl, 1 M NaCl and water (H2O)) was carried out. The strongest band was obtained from sodium chloride (NaCl), potassium chloride (KCl), sodium sulphite buffer (SSB), phosphate buffer and lithium chloride (LiCl), respectively. To determine the minimum concentration and delectability of potato leafroll virus (PLRV) and potato virus S (PVS) that can be assessed by RT-PCR, the sap obtained from tubers known to be infected withPLRV and PVS were diluted (1:1, 1:2, 1: 4, 1:8, 1:16 1:32 and 1:64) and tested in RT-PCR. PLRV and PVS bands were observed up to 1:8 in NaCl and phosphate buffer, 1:4 in KCl, SSB and LiCl. However, exceptNaCl, no difference between the intensity of band obtained from other buffers was observed. On the other hand, increasing the cut surfaces of tuber pieces increased the dilution rate of nucleic acid. To determine the efficiency of the NaCl buffer, when a total of 60 dormant tubers (60 days after the harvest) were tested, PLRV and PVS were detected at the rate of 57/60 and 54/60, respectively

Occurrence of Pospiviroid in potato, tomato and some ornamental plants in Turkey

In order to investigate the Pospiviroid in potato, tomato and some ornamental plants in Turkey, a survey study was carried out from 2006 to 2009. During this survey study, a total of 1766 samples (1047potato samples, 258 tomato leaves and 461 ornamental plants) were tested by reverse transcriptionpolymerase chain reaction (RT-PCR) and, the samples found to be positive in RT-PCR were also checked in return polyacrylamide gel electrophoresis (R-PAGE). Of these samples, potato tubers were collected from markets, leaf samples from potato fields (Erzurum), tomato samples from field (Tokat, Amasya, Balýkesir and Bursa) and greenhouses (Antalya and Mula), leaves and vines of ornamental plants from greenhouses (Yalova) and florists (Erzurum) and recreation areas (Ankara, zmir and Trabzon). In the result of RT-PCR test, PSTVd was detected in 6 out of 891 potato tubers and CSVd in 2out of 154 chrysanthemums. On the other side, tomato, citrus and most ornamental plants belonging to different families were found to be free from pospiviroid. This is the first report of CSVd in Turkey

Why does a metal-superconductor junction have a resistance?

This is a tutorial article based on a lecture delivered in June 1999 at the NATO Advanced Study Institute in Ankara. The phenomenon of Andreev reflection is introduced as the electronic analogue of optical phase-conjugation. In the optical problem, a disordered medium backed by a phase-conjugating mirror can become completely transparent. Yet, a disordered metal connected to a superconductor has the same resistance as in the normal state. The resolution of this paradox teaches us a fundamental difference between phase conjugation of light and electrons.Comment: 12 pages, 5 postscript figures [v2: all figures inline

Advance Artificial Neural Network Classification Techniques Using EHG for Detecting Preterm Births

Worldwide the rate of preterm birth is increasing, which presents significant health, developmental and economic problems. Current methods for predicting preterm births at an early stage are inadequate. Yet, there has been increasing evidence that the analysis of uterine electrical signals, from the abdominal surface, could provide an independent and easy way to diagnose true labour and predict preterm delivery. This analysis provides a heavy focus on the use of advanced machine learning techniques and Electrohysterography (EHG) signal processing. Most EHG studies have focused on true labour detection, in the window of around seven days before labour. However, this paper focuses on using such EHG signals to detect preterm births. In achieving this, the study uses an open dataset containing 262 records for women who delivered at term and 38 who delivered prematurely. The synthetic minority oversampling technique is utilized to overcome the issue with imbalanced datasets to produce a dataset containing 262 term records and 262 preterm records. Six different artificial neural networks were used to detect term and preterm records. The results show that the best performing classifier was the LMNC with 96% sensitivity, 92% specificity, 95% AUC and 6% mean error

Diversité des insectes actifs au sol dans quatre écosystèmes de bas-fonds du Burkina Faso : importance pour la détermination de bio-indicateurs caractérisant ces milieux

L'action de l’Homme sur l'environnement peut affecter la diversité biologique qui à son tour peut être utilisée comme indicateur de la santé des écosystèmes. Une étude a été menée en 2006 dans quatre (4) MicroBassin-Versants (MBV) du Burkina Faso pour évaluer la diversité des insectes rampants au sol et caractériser chaque écosystème par ses bio-indicateurs les plus significatifs. La diversité taxonomique des espècesd’insectes capturées dans différents sites par des pièges de Barber, leur distribution et leur abondance relative au début et à la fin de la saison des pluies ont ainsi été déterminées. Quatre (4) ordres regroupant treize (13)familles d’insectes, les Carabidae, les Scarabaeidae, les Tenebrionidae, les Cétonidae, les Cérambycidae, les Curculionidae, les Hydrophilidae, les Elateridae, les Staphylinidae, les Chrysomelidae (Coléoptères), lesFormicidae (Hyménoptères), les Gryllidae (Orthoptères) et les Labiduridae (Dermaptères), ont été identifiées dans les MBV étudiés. Les variations climatiques influencent la diversité taxonomique des insectes qui fluctuepar ailleurs dans l’espace et dans le temps. Cinq (5) familles, les Formicidae, les Cicindellidae, les Carabidae, les Scarabaeidae et les Tenebrionidae ont été les plus abondantes et les plus diversifiées en espèces dans chacun des quatre MBV. Ces taxa, qui se sont adaptés aux écosystèmes étudiés, en sont probablement les meilleurs indicateurs. Les résultats obtenus sont discutés en vue de déterminer comment ces groupes majeurs peuvent être utilisés dans l’évaluation et la gestion des écosystèmes qu’ils peuplent

Evaluation of advanced artificial neural network classification and feature extraction techniques for detecting preterm births using ehg records

Globally, the rate of preterm births is increasing and this is resulting in significant health, development and economic problems. Current methods for the early detection of such births are inadequate. However, there has been some evidence to suggest that the analysis of uterine electrical signals, collected from the abdominal surface, could provide an independent and easier way to diagnose true labour and detect when preterm delivery is about to occur. Using advanced machine learning algorithms, in conjunction with electrohysterography signal processing, numerous studies have focused on detecting true labour several days prior to the event. In this paper however, the electrohysterography signals have been used to detect preterm births. This has been achieved using an open dataset that contains 262 records for women who delivered at term and 38 who delivered prematurely. Several new features from Electromyography studies have been utilized, as well as feature-ranking techniques to determine their discriminative capabilities in detecting term and preterm records. Seven artificial neural network algorithms are considered with the results showing that the Radial Basis Function Neural Network classifier performs the best, with 85% sensitivity, 80% specificity, 90% area under the curve and a 17% mean error rate. © 2014 Springer International Publishing Switzerland

Advanced Artificial Neural Network Classification for Detecting Preterm Births Using EHG Records

Globally, the rate of preterm births are increasing, thus resulting in significant health, development and economic problems. Current methods for the early detection of such births are inadequate. Nevertheless, there has been some evidence that the analysis of uterine electrical signals, collected from the abdominal surface, could provide an independent and easier way to diagnose true labour and detect when preterm delivery is about to occur. Using advanced machine learning algorithms, in conjunction with Electrohysterography signal processing, numerous studies have focused on detecting true labour several days prior to the event. However, in this paper, the Electrohysterography signals have been used to detect preterm births. This has been achieved using an open dataset, which contains 262 records for women who delivered at term and 38 who delivered prematurely. Several new features from Electromyography studies have been utilized, as well as feature-ranking techniques. Features are ranked to determine their discriminative capabilities in detecting term and preterm records. Seven different artificial neural networks were then used to identify these records. The results illustrate that the Radial Basis Function Neural Network classifier performed the best, with 85% sensitivity, 80% specificity, 90% area under the curve and a 17% mean error rate

Three "universal" mesoscopic Josephson effects

1. Introduction 2. Supercurrent from Excitation Spectrum 3. Excitation Spectrum from Scattering Matrix 4. Short-Junction Limit 5. Universal Josephson Effects 5.1 Quantum Point Contact 5.2 Quantum Dot 5.3 Disordered Point Contact (Average supercurrent, Supercurrent fluctuations)Comment: 21 pages, 2 figures; legacy revie

Estrogenic and Anti-Inflammatory Activities of a Steroidal Indoxyl

The estrogenic and anti-inflammatory activities of 3-methoxy-16, 17-seco-16-norestra-1,3,5-trien-15-(2'-indoxyliden)-17-oic acid is reported. After intraperitoneal administration, the dose of this compound required to reduce swelling of the rat paw by 50% (ED50) was 14.1 mg/kg using the carrageenan-induced rat paw oedema anti-inflammatory assay method. Indomethacin had an ED50 of 3.2 mg/kg in this assay while dexamethasone had an ED50 of 1.7 mg/kg. The estrogenic activity of the compound after intramuscular administration in rats was 0.72 relative to diethylstilbestrol, when the two compounds were assayed at three dose levels of 1.0, 0.3 and 0.1 mg/kg. Key Words: Steroidal indoxyl, synthesis, estrogenic, anti-inflammatory East and Central African Journal of Pharmaceutical Sciences Vol.5(3) 2002: 44-4